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Responsibilities AI Use Cases & Automation Delivery Identify and prioritize AI/automation opportunities , map current vs. future processes, and define clear business requirements across functions (e.g., exception handling, document processing, service operations, billing/audit, reporting) Develop and configure AI prototypes/solutions using modern AI tools and platforms (e.g., LLM apps/agents, RAG, document processing), then iterate into production-ready delivery with internal IT/engineering teams Help identify where workflow automation/low-code tools can streamline processes (e.g., approvals, data analysis, exception management) and support requirement definition, testing, and rollout Hands-on build automations where appropriate; validate solution quality through testing and UAT support with clear documentation Apply AI for document processing, data extraction, classification, decision support, and workflow optimization; ensure solutions are measurable (cycle time, accuracy, cost savings) • Run discovery with business stakeholders, design , build, and ship AI-powered applications end-to-end — from prototype to production • Ensure responsible AI and operational readiness: data privacy, access control, auditability, monitoring, and clear handover/support procedures System Integration (Enterprise Applications & Data) Build and maintain system integrations between AI solutions and enterprise systems (e.g. finance/accounting platforms, and—where applicable—TMS/WMS etc.) via APIs, files, or EDI Work with internal IT/security teams to ensure appropriate access control, data privacy, and compliance requirements are met for each solution Cloud, Data & AI Platform Skills Familiarity with cloud and AI platforms used to deliver enterprise solutions (Azure preferred; other major clouds are a plus) Familiarity with low-code/workflow tools (e.g., Power Platform); ability to translate business needs into configurable solutions matters most Collaboration, Training & Change Management Partner with business team to identify opportunities and prioritize AI/automation backlog based on business value Create and maintain technical documentation, SOPs, and user guides; ensure solutions are supportable. Run knowledge-transfer and training sessions to drive adoption; communicate changes and collect feedback for continuous improvement Requirements Technical & Domain Solid understanding of AI/LLM concepts and practical application (prompting, grounding, evaluation, and limitations) Solid technical skills to support development and troubleshooting (e.g., Cloud, Coding, SQL, API concepts) Ability to build AI solutions and automations (prototype to small production use cases) using modern, best-fit tools/platforms; comfortable learning new AI tools quickly Understanding of data and integrations (e.g., files/CSV, APIs) is; deeper technical skills can be learned on the job Awareness of security and access concepts (e.g., permissions, roles) is a plus Comfortably working with business and IT teams in an enterprise environment; exposure to cloud-based solutions is a plus Understanding of logistics and finance processes is a strong plus (helps translate operational needs into scalable automations) Data literacy: ability to work with structured data, understand KPIs, and validate outputs; Power BI/SQL is a plus Logistics experience is a plus, but learning ability and attitude are more important than full expertise Learning & Ownership Expectations (Important) Self-learner with strong willingness to learn AI, automation, and cloud technologies Able to learn from documentation, examples, and hands-on practice Take responsibility for assigned tasks and follows through to completion Proactively asks questions when unsure instead of waiting passively Willing to improve solutions based on feedback and lessons learned Education & Experience Bachelor’s degree in Computer Science, Artificial Intelligence, Data Science , Information Systems, Supply Chain, or a related field (or equivalent practical experience) 2-5 years of relevant experience (internships, graduate programs, or project experience in AI, process improvement, automation, analytics, or related areas are welcome) If you have the energy and qualifications to add to our velocity, Please visit KLN Company Webpage to apply or send your CV with your present and expected salary to Human Resources & Administration Department by clicking Quick Apply . (We are an equal opportunity employer and welcomes applications from all qualified candidates. All personal data will be kept in the strictest confidence and will be used for recruitment purpose only. All applicants maybe considered for other suitable positions in KLN. All personal data of unsuccessful candidates will be destroyed.)
Here's how to pick the right one and stand out in your application.
144.883Jobs
31.687IN
81%EN
That number is real. WorkMundi's database shows 144,883 open engineer roles across the world. India has the most with 31,687 jobs, followed by the United States with 30,084. If you just finished reading one job ad and felt paralyzed by choice, you're not alone—but this scale is actually an advantage. It means you can afford to be selective.
Start by geography and language. The majority of engineer ads—117,837 of them—have the job posting text written in English. Use that as one filter, but remember: the ad text language tells you nothing about whether the role actually requires you to speak English day-to-day. Read the job description carefully. Then check which countries have the volume you're targeting. Singapore, Poland, and Australia round out the top five after India and the US.
Next, learn who's hiring. Accenture has posted 2,801 engineer roles. andurilindustries, speechify, and jobgether are also actively recruiting. If you're applying to one of these names, research their hiring patterns and interview style before you apply. That homework pays off.
When you interview, expect the question every engineer hears: 'Tell me about a time you had to debug a problem that wasn't in your job description.' Have a specific story ready—not a general one. Name the tools, the deadline pressure, and what you learned. Hiring managers listen for whether you see problem-solving as part of the role itself, not a favour.